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Статья

A heuristic adaptive fast gradient method in stochastic optimization problems

A fast adaptive heuristic stochastic gradient descent method is proposed. It is shown that this algorithm has a higher convergence rate in practical problems than currently popular optimization methods. Furthermore, a justification of this method is given, and difficulties that prevent obtaining optimal estimates for the proposed algorithm are described.